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Questions tagged [odds-ratio]

A measure of association between two binary variables equal to the odds of a 'positive' outcome in 1 variable divided by the odds in the other. The OR ranges (0, infinity). It has a strong connection to logistic regression.

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logit model - labor probability(odds ratio) [duplicate]

The logit model is given: $$ \text{Labor probability} = \alpha + \beta_1 \cdot \text{income} + \beta_2 \cdot \text{age} + \beta_3 \cdot \text{education} + \beta_4 \cdot \text{young kids} + \beta_5 \...
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What are the issues with absolute risk reduction/relative risk reduction vs odds ratios in reference to variation over risk factors

The following quote is from this: Any measure that has the potential for summarizing a treatment effect with one constant for all types of patients will be non-collapsible when the outcome is ...
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Is there an way to model random effects in a design that is typically analyzed by the McNemar test?

My question is: if in a study with paired binary response data (where McNemar test is often used) we can use the exact binomial test to test the odds ratio, is it possible to model the same odds ratio ...
jeffalltogether's user avatar
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Plotting interaction by logistic regression

I have used R to plot the interaction term from the logit function I computed. I use the standard cat_plot() to plot the interaction. I clearly see that the two ...
Devi Sita's user avatar
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How to convert odds ratio to cohens d [duplicate]

I want to calculate the cohens d from adjustad OR, but I think I'm doing something wrong. If aOR = 1.79, N = 600, N_case = 298, N_control = 302, then is the cohen's d 0,139 or 0,321? What formula did ...
Brandy Wise's user avatar
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Binary logistic regression: why do these two coefficients have opposing signs when they are indicators of the same outcome?

I hope someone can help me understand why this is happening. Reproducible example in R: ...
Reader 123's user avatar
4 votes
1 answer
116 views

Sample size calculation for proportional odds model

Apologies in advance for my lack of statistical knowledge/insight! I am trying to calculate the sample size for a clinical trial of treatment A versus placebo with primary outcome of prolongation of ...
Catherina Muscat's user avatar
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Meta-analysis of odds ratio for continuous variables, how to interpret the decrease or increase per unit?

So, I am doing a meta-analysis of odds ratios to find out the risk factors for a certain medical outcome. One of those risk factors would be (simplified) the time spent in the operation room. My ...
echodoro's user avatar
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Estimate subgroup sizes with a a given OR including CI and total sample sizes

We are doing a meta-analysis using OR as the effect size, but on a limited number of trials. The data is a bit messy and some numbers are missing - at least for our purposes. I was wondering if there ...
umrpedrod's user avatar
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Checking my interpretation of the odds ratio in OLR [duplicate]

I have run an ordinal logistic regression (response variable is "classification" with three ordered levels: control, intermediary group, and disease group). The predictor variable is a ...
Cam_stats's user avatar
6 votes
1 answer
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What is the best statistical test to compare the survey Response rate for a control and treatment group?

We run a survey and want to run a controlled test on a sample of the data. The measure we are trying to improve is response rate. Our research question is: “does sending out more invites to ...
user411368's user avatar
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Odds Ratios paradox? Pooled OR inconsistent with subgroup ORs

I have two groups (A and B) that each produce ORs of 1.44 and 1.50. However, if I combine the frequencies for the two groups to create a pooled dataset, I get an OR of 1.40. I get that it's not going ...
S Robidoux's user avatar
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determining if odds-ratio for a numerical x variable and binary y label in logistic regression differs between groups (ie. gender or race) [duplicate]

I've seen people ask a similar question, but I'm still not super clear what the best recommendation would be - I am looking at a binary dependent variable, and multiple independent variables (some of ...
mz.'s user avatar
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Scaling the odds-ratio of a binary logistic regression

Just a quick one - to put it simply, I am conducting a study regarding age and marriage. I have found that with a binary logistic regression (dependent variable yes/no to being married), the odds-...
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Binomial logistic regression and inter-group comparison

I am interested in exploring the relationship between two categorical variables: "Ethnicity" and "Disease", each with two levels. My primary hypothesis is that individuals with &...
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Can you derive the standard error of odds ratio, from a method (Kraemer and Kupfer) that derives Risk Difference (and its SE) from continuous data?

Let's say that we have a RCT trial going on and the outcome is a continuous variable. In this paper https://pubmed.ncbi.nlm.nih.gov/23045205/ there are 4 methods that calculate approximated odds ...
SpartacusKD's user avatar
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interpreting logistic regression output: how to relate predicted values to coefficients [duplicate]

I see many questions on this topic, but I promise none seem to explain what I'm after. I want to understand how to tie the coefficients I get from a logistic regression model back to the model ...
vvv's user avatar
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Calculating odds ratios for an interaction term

Ratgrp stands for lung function (FEV1/FVC)*100 and it has two categories: 1: Lung function less than 70 2: Lung function equal and higher than 70 ...
Jonathan's user avatar
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Odds ratio direction changes in multinomial logistic regression

I am doing a multinomial logistic regression in R for an outcome variable with four categories, and 9 categorical independent variables. My dataset contains 1408 observations. When I run the model ...
Maria's user avatar
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Crude multivariate binomial regression OR vs univariate binomial regression OR?

I've performed an univariate binomial regression with OR (95% CI) and I obtain this result: ...
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Is it possible to give a single Odds Ratio for two independent variables?

I have been asked by co-authors on a paper to fill in the Odds Ratios marked as (?) in a table like the one below. Country of origin Land A (Odds Ratio) Land B (Odds Ratio) Number of people who meet ...
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Logistic regression: restrict the prediction range [duplicate]

I am running a basic logistic regression with a single independent variable (X) and one dependent variable (y). In the accompanying figure, the logistic regression predicts values that tend to 0 and 1 ...
Fra's user avatar
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1 answer
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Interpreting Fisher's exact test OR, CI and p-values

In the context of Fisher's exact test results, it seems that a bunch of online tutorials mainly focus on interpreting the p-value exclusively, without considering the confidence intervals or the odds ...
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Ordinal Logistic Regression SPSS Interpretation

I have data from a questionnaire study structured like so: Age - Ordinal (18-24, 25-34, 35-44, 45-54, 55+) Gender - Nominal (Male, Female) AnxietyType - Nominal (Self-diagnosed, Professionally ...
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Find the impacts of alleles on the intensity of a disease

I have a dataset, I attach a sample of my data and the code. I have one column which shows the intensity value of a disease, one column which shows that its weak of moderate and the other columns are ...
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Modelling of odds ratio with continuous & categorical covariates

We've completed a systematic review of % diagnosed among female sex workers (FSW) living with HIV across Sub-Saharan Africa (SSA). In our Objective 1, we model this proportion $p_s$ as: \begin{aligned}...
jessexknight's user avatar
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Comparing significance of categorical levels in logistic regression

I'm running a logistic regression on some data that has a binary outcome and several input variables, one of which is categorical with 5 levels. I'm using one of these levels as the reference, and so ...
k13's user avatar
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Regression analysis with single outcome variable and binary independent variables

This is a meta-analysis. I'm looking at factors associated with vaccine acceptance in many countries. Looking at previous studies in different countries, I recorded factors that are associated with ...
Jerome Dinga's user avatar
5 votes
1 answer
172 views

What references discuss the problems with phi as an association measure?

(Olivier (2013) states that many have pointed out problems with $\phi$ as an association measure and advocate the use of odds ratios as an alternative Unfortunately, it does not give citations for ...
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Psuedo-"Odds ratio" for multiple columns

I have a dataset with a categorical target ($y$) and multiple categorical features ($x_1$, $x_2$, ..., $x_i$). I have been able to successfully use a logistic regression model to calculate an odds ...
User81646's user avatar
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Interpretation of an interaction effect (ratio of odds ratios) when using effect coding

I ran a multilevel logistic regression model using function glmer from R package lme4. All of my predictors are binary and I have used effect coding, i.e., coding -...
Michael Krah's user avatar
3 votes
2 answers
156 views

Why are my odds ratio confidence intervals so wide?

I'm pretty new to categorical data analysis. I'm trying to understand why my confidence intervals are so wide, I've never seen CI's this wide. From what I'm reading online this is mostly related to ...
Michele's user avatar
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2 votes
1 answer
289 views

How to interpret odds ratios by emmeans for glmmTMB-beta

I fit this mixed model with beta for the response variable: photochemical efficiency or Fv/Fm and the predictor variables are categorical: ...
Franelibethgalvez's user avatar
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1 answer
39 views

Logistic regression odds vs Survival analysis odds

Why do I get significantly different answers from the logistic regression and survival analyses? How can I fix this code? Logistic regression: ...
Nim's user avatar
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How to convert Standarized Mean Difference to OR in skewed data?

There are many methods to convert Standarized Mean Differences to Odds Ratios for meta-analysis (ln(OR) = -1.8 SMD), but none that i have found really deals with skewed summary data. Do you think i ...
san festein's user avatar
4 votes
1 answer
339 views

Is it appropriate to present predicted probabilities from emmeans for a mixed-effects binomial logistic regression?

I am trying to understand how to analyze data for a generalized mixed model (GLMM) with a binary response. I am interested in visualizing the predicted probabilities, as well as a measure of effect ...
user398696's user avatar
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Interpreting normalized value in logistic regression

I'm trying to interpret results from my logistic regression. I normalized the values between 0 and 100 because I had many variables with different units. My intercept is -0.741 and I'm using that to ...
imane fouiteh's user avatar
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37 views

Mixed beta regression interpretation with categorical predictor

I have run mixed beta regressions on proportional data but I am struggling in my interpretation of the results. I understand this has been asked before but I have a categorical predictor with four ...
ScottM10's user avatar
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16 views

English meaning of risk vs odds? [duplicate]

I am trying to learn more about the difference between risk vs odds (e.g. relative risk, odds ratio). Since English is not my first language, these words have identical meanings to me: Smokers have ...
stats_noob's user avatar
2 votes
1 answer
72 views

Is it possible to perform a meta-analysis of multiple outcomes and multiple predictors?

I have a pool of 20-ish quantitative studies that report odds ratios for a particular outcome (e.g. homelessness) but most studies will also report a few more outcomes. All of these studies report the ...
brendans-bits's user avatar
2 votes
1 answer
48 views

Can I do a Meta-Analysis for Odds Ratio's for continuous predictor (age) with Binary outcome (Affliction, yes or no) in R?

I'm looking for a way to conduct a Meta-analysis on Odds Ratio's from several studies/article's. The thing is that my OR's are based on logistic regression's with continuous predictors (outcome is ...
Benjamin Telkamp's user avatar
2 votes
0 answers
11 views

Why marginal odds in frequency matched case-control?

Let $D$ denote sampling with $D=1$ indicating subject being sampled and $D=0$ otherwise. $W$ denotes intrinsic variable of subjects, $X$ denotes exposure of interest and $Y$ denotes the binary outcome....
user45765's user avatar
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Correct interpretation of a logistic regression coefficient

I have a simple confusion regarding the interpretation of logistic regression. Suppose married people are more likely to be employed compared to single people. In here, unemployment = 0, employment = ...
Prasanna's user avatar
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2 answers
194 views

Odds and expected value in betting

I'm reading an article about expected value in betting, I got stuck at the very beginning: Let’s use a coin toss as an example of calculating expected value. Assuming the coin and the toss are fair, ...
Juan's user avatar
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Risk ratio or odds ratio?

I have a question which may seem stupid. This is for a retrospective cohort study. I have a table like this for my outcome: Among the 20,000 patients in group A, 4671 are dead (23.55%). Among 50,000 ...
user19745561's user avatar
1 vote
0 answers
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Calculating Odds ratio with exclusion criteria

I had a question about how to perform an odds ratio when the group has an exclusion criterion. Let's say I am trying to find the association between surgery and suicide. I wanted to control for people ...
Bob's user avatar
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1 answer
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Odds Ratio or 2 Prop Z Test

We would like to conduct an AB Test between 2 groups of people and the apps that people have to see which ones over or underindex. Which is more appropriate odds ratio or 2 proportional z test and why?...
Hider1466's user avatar
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30 views

Computing odds ratios for multiple dichotomous DVs in a within-person, mixed-effects design?

I have an experiment where people participate in a series of tasks (say 4) and then are scored based on their performance (pass/fail). The order of the tasks is randomized. I want to predict ...
socialresearcher's user avatar
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57 views

Univariate odds ratio calculation - by hand versus log regression

If I have only one binary predictor variable for a binary outcome, is there any meaningful difference between doing hand calculation of odds ratio (OR = ad/bc), versus doing a univariate logistic ...
zappbran's user avatar
2 votes
1 answer
94 views

What are the comparative advantages and disadvantages of interpreting regression output using marginal effects vs. ratios?

In models with a discrete dependent variable and/or linear models with non-linear right-hand specifications (interactions, polynomials, etc.), interpreting the association between Y and BX becomes ...
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